Assessing Weather-Yield Relationships in Rice at Local Scale Using Data Mining Approaches.

ABSTRACT: Seasonal and inter-annual climate variability have become important issues for farmers, and climate change has been shown to increase them. Simultaneously farmers and agricultural organizations are increasingly collecting observational data about in situ crop performance. Agriculture thus needs new tools to cope with changing environmental conditions and to take advantage of these data. Data mining techniques make it possible to extract embedded knowledge associated with farmer experiences from these large observational datasets in order to identify best practices for adapting to climate variability. We introduce new approaches through a case study on irrigated and rainfed rice in Colombia. Preexisting observational datasets of commercial harvest records were combined with in situ daily we

SUBMITTER: Delerce S 

PROVIDER: S-EPMC4999131 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature